"Should I use Google or Meta?" is one of the most common questions we hear from new clients. It is almost always the wrong question. The right question is: "How do I use both platforms to capture demand at every stage of the buying journey?" The businesses achieving 6x to 10x blended ROAS are almost universally running both channels in a coordinated strategy. The businesses stuck at 2x to 3x are usually committed exclusively to one or the other.

How the Two Platforms Differ Fundamentally

Google Search operates on declared intent. Someone types "best Meta Ads agency London" into Google. That query is an explicit, high-intent signal. Your ad appears in response to an active decision to find something. You are competing for attention at the moment of maximum readiness to engage. Conversion rates on Search tend to be high. CPCs are higher because every advertiser in your category is competing for the same intent signals.

Meta operates on interruption. Your ad appears in a feed where someone is consuming content about their friends, interests, and entertainment. They were not looking for your product. Your ad needs to interrupt their current mental state and create interest that did not previously exist. This is harder — but it allows you to reach people who need your product but would never think to search for it.

Audience Intent Spectrum: High Intent Google vs Discovery Meta

The buyer's journey exists on an intent spectrum, and different platforms capture different points: Awareness stage (Meta dominates): The prospect does not yet know they have a problem or that a solution exists. Meta's interest targeting and lookalike audiences reach people at this stage. Consideration stage (Meta/Google Display): The prospect knows they have a problem and is researching solutions (but not yet searching). Meta retargeting and Google Display capture this stage. Decision stage (Google dominates): The prospect is ready to buy and is actively searching for specific solutions. Google Search captures this stage at maximum intent. Loyalty stage (Meta/Email): The prospect has purchased and you need to retain them and encourage repeat purchase.

Understanding where your buyers are in their journey determines which platform leads your strategy. A typical B2C e-commerce journey might be: 6 weeks of Meta awareness (building familiarity with your brand and product), 2 weeks of Google search (comparing your brand against competitors), 3 days of retargeting across both platforms (addressing final objections), then purchase. A B2B service journey might be: 8 weeks of Google display and LinkedIn (awareness in a context where professionals are researching), 4 weeks of Google search (active evaluation), then final decision (often on a phone call or sales-assisted channel, not in ads).

When Google Wins and When Meta Wins

Google wins when: your category has high search volume (the prospect is actively searching for your solution), your average order value is above £200 (making Search CPC economically viable), your product solves an acute, immediate problem that buyers search for actively, and your sales cycle is short (buyers make decisions quickly after searching).

Meta wins when: your product solves a problem buyers have not yet named (they do not search for your solution category), you are in a visually compelling category (fashion, beauty, food, lifestyle), your average order value is lower and requires high-volume customer acquisition, or you are building brand awareness in a new market where search volume does not yet exist.

For most e-commerce businesses, the optimal structure is Meta-led with Google Search for branded terms and high-intent queries. For most service businesses with established category search volume, the optimal structure is Google-led with Meta used for retargeting and brand awareness.

Industry-by-Industry Budget Split Recommendations

E-commerce (physical products): Optimal split 60% Meta / 40% Google. Meta builds awareness and uses interest targeting and lookalikes to find cold audiences. Google captures searchers ready to buy. SaaS (software): Optimal split 40% Meta / 60% Google. Most SaaS buyers search for solutions categories actively (project management tools, marketing automation). Google captures this high-intent audience. Meta is used for retargeting and building awareness among broader audiences who may not yet be searching. Local services (plumbing, dentistry, legal): Optimal split 20% Meta / 80% Google. Local service buyers search aggressively for providers in their area. Google Local Services Ads dominates this channel. Meta is used for reputation building and local awareness. Coaching/Education: Optimal split 70% Meta / 30% Google. Coaching buyers often do not search for the category (they are not yet aware they need coaching). Meta reaches them via interest targeting (personal development, specific problems they face). Google captures the 30% who are searching for solutions. B2B Services (consulting, agencies): Optimal split 30% Meta / 70% Google. B2B buyers use Google to research service providers in their category. LinkedIn and Google are the primary channels. Meta is secondary, used for awareness and retargeting among prospects identified through Google.

Using Google Data to Improve Meta Targeting

Google Search query data reveals the exact language and intent signals your customers use when they are in buying mode. This is invaluable for Meta: if your highest-converting Google search query is "affordable project management software for small teams," this exact phrase is a goldmine for Meta targeting. Use this language in Meta ad copy and creative hooks — the words your customers use on Google are the same words that resonate emotionally on Meta.

Reverse the flow: Meta audience interest and demographic data tells you which messaging resonates with your audience in discovery mode. If a Meta creative about "save 5 hours per week with automation" outperforms other variations by 2x, this message insight should inform your Google Search copy and Landing page messaging. Customers who see this hook on Meta and become aware of your solution category will later search using this language on Google — and your Google ads should mirror the message that created initial interest.

The Attribution Overlap Problem Between Channels

The moment you run both Google and Meta simultaneously, attribution becomes complicated. A customer who sees a Meta ad on Monday, searches your brand on Google on Thursday, and purchases on Friday will be claimed by both platforms. Google's last-click attribution will give 100% credit to the brand search. Meta's view-through attribution will claim credit for the initial exposure. Your actual CPA, reported by each platform, will be understated because each platform is claiming conversions the other partially generated.

The solution: measure blended ROAS (total revenue divided by total ad spend across both platforms) as your primary performance metric. This eliminates cross-platform attribution overlap. Use platform-specific data only for intra-platform optimisation — identifying which specific campaigns, ad sets, and ads within each platform are performing relatively better or worse than others in the same channel. Example: if Google shows 4 branded keywords and Meta shows 6 ad sets, use Google's keyword performance data to reallocate budget among keywords, and Meta's ad set data to reallocate among ad sets. But use blended ROAS to make decisions about total platform allocation.

When to Run Both vs Just One

Run both when: you have a minimum monthly budget of £3,000+ (allowing meaningful allocation to both platforms), your business model benefits from both awareness-stage and decision-stage demand (most do), you want to reduce platform risk (being reliant on one platform exposes you to algorithm changes), you have the operational capacity to manage two different campaign structures and reporting systems.

Run only one when: your budget is under £2,000/month (concentrating on one platform is more efficient at low scale), your market has extremely high or low search volume (zero search volume = Meta only; extremely high search volume where Meta is ineffective = Google only), you are a service business in a highly commoditised category where every customer searches (Google-only strategy is optimal for lawyer, dentist, plumber categories).

The Combined Channel ROAS Model

Building a combined channel model that predicts blended ROAS based on platform allocation: Step 1: Measure your Google Search ROAS historically at current spend levels. Let's say 4× ROAS. Step 2: Measure your Meta ROAS historically at current spend levels. Let's say 2.5× ROAS. Step 3: Account for cross-channel attribution: Google's 4× is overstated by approximately 20% (it is claiming some Meta-assisted conversions). Adjusted Google ROAS: 3.2×. Meta's 2.5× is understated by approximately 15% (it is not getting credit for awareness it creates). Adjusted Meta ROAS: 2.875×. Step 4: If you allocate 40% of budget to Google (3.2× ROAS) and 60% to Meta (2.875× ROAS), your blended ROAS model predicts: (0.40 × 3.2) + (0.60 × 2.875) = 2.94× blended ROAS. Step 5: Run the allocation for 30 days and compare actual blended ROAS to the model. If the model is accurate, you can adjust allocations using this framework. If actual results deviate, it reveals where your assumptions about platform performance are inaccurate.

Building a 90-Day Experiment to Find Your Optimal Split

Theory provides starting points. Data provides answers. Run a 90-day structured experiment: Month 1 — allocate 70% Google, 30% Meta. Measure blended ROAS, total revenue, and new customer acquisition. Month 2 — shift to 50/50. Measure the same metrics. Month 3 — shift to 30% Google, 70% Meta. The allocation that produces the highest blended ROAS and the best new customer acquisition efficiency becomes your baseline. Refine quarterly from there as market conditions and platform performance evolve.

The businesses that find their optimal channel mix and commit to it with conviction — rather than constantly switching strategies based on individual platform dashboards — are the ones compounding performance year over year. Discipline in execution, combined with systematic measurement, is what separates the top 5% of advertisers from the rest.

Attribution in a Multi-Channel World

The attribution challenge in Google-Meta combined strategies is not just a measurement inconvenience — it can fundamentally mislead budget allocation decisions. Consider a common scenario: a customer first sees a Meta ad (awareness), later searches for your brand on Google (intent), and purchases through a Google brand search ad. Google's last-click attribution gives 100% of the credit to the brand search campaign. Meta's view-through attribution gives credit to the original awareness ad. Both platforms show strong ROAS. If you pause Meta believing it is redundant, you may find that branded search volume drops 30 to 40% — because Meta was driving the demand that Google was capturing.

The solution is not better attribution technology — it is direct experimentation. Run a Meta spend holdout test: reduce Meta spend by 50% for 30 days and observe what happens to branded search volume and total revenue. The counterfactual tells you what Meta's true contribution is in a way that no attribution model can. This test should be run annually, or whenever you are making significant changes to channel mix decisions.

The Search Intent Creation Flywheel

The most powerful dynamic in a well-coordinated Google-Meta strategy is what we call the search intent creation flywheel: Meta awareness ads create latent brand awareness and category interest → this awareness converts into branded and category search queries over time → Google captures these queries with Search campaigns → the high purchase intent of Google searchers produces strong ROAS → Google ROAS justifies scale → scale creates more awareness that feeds back into the flywheel. As the flywheel accelerates, the efficiency of both channels improves because each is strengthening the other.

To measure the flywheel effect: track branded search query volume over time correlated with Meta spending. When Meta spend increases, branded search volume should increase with a 2 to 4-week lag (the time it takes for awareness to translate into search behaviour). When Meta spend decreases, branded search volume should decline with the same lag. This correlation, measured over 6+ months, quantifies the cross-channel value that Meta is generating and justifies Meta investment even when its in-platform ROAS appears lower than Google's.

Audience Intelligence Sharing Between Platforms

The most sophisticated multi-channel strategies use insights from each platform to improve performance on the other. Google Search query data reveals the exact language and intent signals your customers use when they are in buying mode. This data is invaluable for Meta ad copy: the queries that convert on Google contain the specific words and phrases that resonate with high-intent buyers. Incorporating these exact phrases into Meta hook copy and body copy bridges the gap between the awareness and intent stages more effectively than generic benefit language.

Conversely, the audience interest and demographic data available through Meta's creative testing (which audiences respond to which messages, which emotional triggers are most effective for your category) informs Google Display and YouTube targeting. The creative insights from Meta testing tell you which messages work for your audience in a passive consumption context — which is the same context as Google Display and YouTube pre-roll. Running multi-channel campaigns with shared creative and messaging insights creates a coherent brand experience across every touchpoint in the customer journey and compounds the familiarity effects that drive higher conversion rates at every stage.

Measuring Cross-Channel Synergy: The True Cost of Channel Attribution

The most sophisticated multi-channel measurement approach: track incrementality, not just last-touch attribution. Run a 30-day holdout test: reduce one channel (Meta) by 50% while maintaining the other (Google) at full spend. Measure: does total revenue decline, or do conversions shift to the maintained channel? If revenue declines less than the budget reduction (50% budget reduction, 30% revenue decline), the reduced channel had synergistic value. The £20 of £100 budget reduction that did not produce £20 of revenue loss represents the synergistic value of that channel — it was creating demand that the other channel captured. Understanding synergy percentage allows for better allocation: if Meta has £50 synergistic value per £100 spent, but £25 direct value, the total value is £75 per £100. This true value should inform budget allocation decisions.

Competitive Positioning: Using Both Channels for Maximum Market Share

The competitive advantage compounds when both channels work together. A prospect encountering your brand on Meta first sees awareness messaging (problem identification, solution awareness). If they later search on Google, they are searching informed by Meta exposure. Your Google brand search ad now appears against a backdrop of existing brand familiarity. Your competitive advantage in that auction is measurable: 15 to 25% higher CTR on brand search when paired with Meta awareness, compared to brand search alone. Competitors running only one channel lack this advantage. Over 12 months, the compounding effect of multi-channel synergy produces 30 to 50% higher revenue per unit of ad spend compared to single-channel strategies.